- Language: en
- Documentation version: 1.3.1
Linear PD model
[Generated automatically as a Tutorial summary]
Model Description
- Name:
linear_pd
- Title:
Linear PD model
- Author:
PoPy for PK/PD
- Abstract:
A simple Linear PD Model.
Model consists of a baseline which increases linearly with concentration.
- Keywords:
pd; linear; one compartment model
- Input Script:
- Diagram:
Comparison
True objective value
-52.6006
Final fitted objective value
-54.1617
Compare Main f[X]
No Main f[X] values to compare.
Compare Noise f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[BL] |
15 |
9.99 |
10 |
6.26e-03 |
0.06% |
f[SLOPE] |
0.5 |
1.04 |
1 |
4.12e-02 |
4.12% |
f[ANOISE] |
5 |
0.463 |
0.5 |
3.74e-02 |
7.47% |
Compare Variance f[X]
No Variance f[X] values to compare.
Outputs
Fitted f[X] values (after fitting)
f[BL] = 9.9937
f[SLOPE] = 1.0412
f[ANOISE] = 0.4626
Generated data .csv file
- Synthetic Data:
Gen and Fit Summaries
Gen: Linear PD model (gen)
Fit: Linear PD model (fit)
Inputs
True f[X] values (for simulation)
f[BL] = 10.0000
f[SLOPE] = 1.0000
f[ANOISE] = 0.5000
Starting f[X] values (before fitting)
f[BL] = 15.0000
f[SLOPE] = 0.5000
f[ANOISE] = 5.0000